With the wide spread of all different types of image taking devices, including digital camera, cell phone, tablet computer and etc, images have been generated exponentially around the world. Now, image becomes an indispensable part of people's daily life, social activity and entertainment. The information included in a single image accounts for a huge quantity of words, and is more direct and more vivid. On the other hand, however, most of these pictures are not in good quality, which significantly affects their utilities. There are many factors accounting for the low quality of these images. Two major ones would be the hardware used for taking the image and the condition under which the image has been taken.
In most of the cases, the conditions under which people are taking pictures are not perfect. For example, the lighting condition may be too low or too high, the imaging device is shaking and so on. The weak signal under the low lighting condition would certainly compromise the image quality. In addition, the image device used for taking picture is not perfect, either. Many of them are not professional or dedicated device for image taking, such as the compact digital camera, cell phone and tablet computer. Currently, millions of digital images are collected using smart phones, iPads, tablets, etc. on a daily basis. Yet many of them are in low quality.
There are a few ways to improve the quality of the images. Of course, one of the most fundamental approaches would be to improve the performance of the image taking device and to adjust the lighting condition of the object. However, such approaches are either very costly (as for the professional image taking device), or infeasible (no way to change the lighting condition). In view of these issues, one of the most economical and effective method for improving image quality would be using an image editing software. The common image editing software comprising the function of denoising includes Adobe Photoshop, Adobe Lightroom, PhotoNinja and so on. However, most of the software is not capable of performing the denoising function in a satisfactory manner. They may either leave too much noise still in the processed image or remove too many details from the original image. Both of them are undesirable to the users.
Moreover, in most cases, these software programs or algorithms require users to choose the values of many parameters, including signal-to-noise ratio (SNR), contrast level, and so on. Nevertheless, for most of the normal users, they are not professional imaging editors. Even though they may understand what those parameters stand for, they still have no clue about what would be the optimal values for those imaging editing parameters, which need quite some experiences and skills or many times of trial and error. As a result, they may either waste certain time on setting those parameters, or just give it up. In light of the above issues, many common users cannot really benefit from such complex image editing software they bought.
In view of the foregoing, one objective of the present invention is to provide a method for denoising image, wherein this method is both easy to use (with no need to set the values of multiple parameters) and of a desirable performance (the resulted denoised image is of desired quality).